1. Field
The present disclosure relates to computer systems and methods in which data resources are shared among data consumers while preserving data integrity and consistency relative to each consumer. More particularly, the disclosure concerns an implementation of a mutual exclusion mechanism known as “read-copy update” in a cache-incoherent shared-memory computing environment.
2. Description of the Prior Art
By way of background, read-copy update (also known as “RCU”) is a mutual exclusion technique that permits shared data to be accessed for reading without the use of locks, writes to shared memory, memory barriers, atomic instructions, or other computationally expensive synchronization mechanisms, while still permitting the data to be updated (modify, delete, insert, etc.) concurrently. The technique is well suited to both uniprocessor and multiprocessor computing environments wherein the number of read operations (readers) accessing a shared data set is large in comparison to the number of update operations (updaters), and wherein the overhead cost of employing other mutual exclusion techniques (such as locks) for each read operation would be high. By way of example, a network routing table that is updated at most once every few minutes but searched many thousands of times per second is a case where read-side lock acquisition would be quite burdensome.
The read-copy update technique implements data updates in two phases. In the first (initial update) phase, the actual data update is carried out in a manner that temporarily preserves two views of the data being updated. One view is the old (pre-update) data state that is maintained for the benefit of read operations that may have been referencing the data concurrently with the update. The other view is the new (post-update) data state that is seen by operations that access the data following the update. In the second (deferred update) phase, the old data state is removed following a “grace period” that is long enough to ensure that the first group of read operations will no longer maintain references to the pre-update data. The second-phase update operation typically comprises freeing a stale data element to reclaim its memory. In certain RCU implementations, the second-phase update operation may comprise something else, such as changing an operational state according to the first-phase update.
FIGS. 1A-1D illustrate the use of read-copy update to modify a data element B in a group of data elements A, B and C. The data elements A, B, and C are arranged in a singly-linked list that is traversed in acyclic fashion, with each element containing a pointer to a next element in the list (or a NULL pointer for the last element) in addition to storing some item of data. A global pointer (not shown) is assumed to point to data element A, the first member of the list. Persons skilled in the art will appreciate that the data elements A, B and C can be implemented using any of a variety of conventional programming constructs, including but not limited to, data structures defined by C-language “struct” variables. Moreover, the list itself is a type of data structure.
It is assumed that the data element list of FIGS. 1A-1D is traversed (without locking) by multiple readers and occasionally updated by updaters that delete, insert or modify data elements in the list. In FIG. 1A, the data element B is being referenced by a reader r1, as shown by the vertical arrow below the data element. In FIG. 1B, an updater u1 wishes to update the linked list by modifying data element B. Instead of simply updating this data element without regard to the fact that r1 is referencing it (which might crash r1), u1 preserves B while generating an updated version thereof (shown in FIG. 1C as data element B′) and inserting it into the linked list. This is done by u1 acquiring an appropriate lock (to exclude other updaters), allocating new memory for B′, copying the contents of B to B′, modifying B′ as needed, updating the pointer from A to B so that it points to B′, and releasing the lock. In current versions of the Linux® kernel, pointer updates performed by updaters can be implemented using the rcu_assign_pointer( ) primitive. As an alternative to locking during the update operation, other techniques such as non-blocking synchronization or a designated update thread could be used to serialize data updates. All subsequent (post update) readers that traverse the linked list, such as the reader r2, will see the effect of the update operation by encountering B′ as they dereference B's pointer. On the other hand, the old reader r1 will be unaffected because the original version of B and its pointer to C are retained. Although r1 will now be reading stale data, there are many cases where this can be tolerated, such as when data elements track the state of components external to the computer system (e.g., network connectivity) and must tolerate old data because of communication delays. In current versions of the Linux® kernel, pointer dereferences performed by readers can be implemented using the rcu_dereference( ) primitive.
At some subsequent time following the update, r1 will have continued its traversal of the linked list and moved its reference off of B. In addition, there will be a time at which no other reader process is entitled to access B. It is at this point, representing an expiration of the grace period referred to above, that u1 can free B, as shown in FIG. 1D.
FIGS. 2A-2C illustrate the use of read-copy update to delete a data element B in a singly-linked list of data elements A, B and C. As shown in FIG. 2A, a reader r1 is assumed be currently referencing B and an updater u1 wishes to delete B. As shown in FIG. 2B, the updater u1 updates the pointer from A to B so that A now points to C. In this way, r1 is not disturbed but a subsequent reader r2 sees the effect of the deletion. As shown in FIG. 2C, r1 will subsequently move its reference off of B, allowing B to be freed following the expiration of a grace period.
In the context of the read-copy update mechanism, a grace period represents the point at which all running tasks (e.g., processes, threads or other work) having access to a data element guarded by read-copy update have passed through a “quiescent state” in which they can no longer maintain references to the data element, assert locks thereon, or make any assumptions about data element state. By convention, for operating system kernel code paths, a context switch, an idle loop, and user mode execution all represent quiescent states for any given CPU running non-preemptible code (as can other operations that will not be listed here). The reason for this is that a non-preemptible kernel will always complete a particular operation (e.g., servicing a system call while running in process context) prior to a context switch.
In FIG. 3, four tasks 0, 1, 2, and 3 running on four separate CPUs are shown to pass periodically through quiescent states (represented by the double vertical bars). The grace period (shown by the dotted vertical lines) encompasses the time frame in which all four tasks that began before the start of the grace period have passed through one quiescent state. If the four tasks 0, 1, 2, and 3 were reader tasks traversing the linked lists of FIGS. 1A-1D or FIGS. 2A-2C, none of these tasks having reference to the old data element B prior to the grace period could maintain a reference thereto following the grace period. All post grace period searches conducted by these tasks would bypass B by following the updated pointers created by the updater.
Grace periods may be synchronous or asynchronous. According to the synchronous technique (e.g., using the synchronize_rcu( ) primitive), an updater performs the first phase update operation, blocks (waits) until the grace period has completed, and then implements the second phase update operation, such as by removing stale data. According to the asynchronous technique (e.g., using the call_rcu( ) primitive), an updater performs the first phase update operation, then specifies the second phase update operation as a callback, and thereafter resumes other processing with the knowledge that the callback will eventually be processed at the end of a grace period. Advantageously, callbacks requested by one or more updaters can be batched (e.g., on callback lists) and processed as a group at the end of the grace period. This allows grace period overhead to be amortized over plural deferred update operations.
Multiprocessor RCU implementations developed to date assume that the underlying hardware system offers cache-coherence and one of a range of memory-ordering models (i.e., from strongly ordered to weakly ordered). However, there have been recent concerns, particularly among vendors offering strongly ordered systems, that cache-incoherent systems will be required in order to continue progress according to Moore's Law. Whether or not these concerns have any basis in reality, shared-memory cache-incoherent systems are starting to appear. In some cases, all caches in the system are incoherent. In other cases, the system may have cache-coherent multi-processor “nodes” within a larger cache-incoherent system. In such systems, cache coherence is maintained with respect to a node's local memory but not with respect to the memory of other nodes. Although there has been some work extending RCU to shared-nothing systems (i.e., clusters), there has been very little work towards efficient RCU implementations in cache-incoherent shared-memory multiprocessor systems. One of the challenges facing RCU in a cache-incoherent shared-memory environment is the need to accommodate the reuse of memory blocks by updaters. Such reuse can occur, for example, when a memory block associated with stale data is reclaimed at the end of a grace period and then subsequently reused for storing new data. If the memory block is reused before the cachelines containing the stale data are removed from local processor caches, readers dereferencing pointers that should point to the new data may in fact retrieve the old stale data.
One prior-art approach for solving this problem, used in the Blackfin® system from Analog Devices, Inc., is to have the rcu_dereference( ) primitive flush all lines from the executing processor's cache. See Linux® v.2.6.39 source code—SSYNC( ) instruction at line 163 of _raw_smp_check_barrier_asm( ) function spanning lines 136-183 of /linux/arch/blackfin/mach-bf561/atomic.S, which is called from smp_check_barrier( ) function spanning lines 59-62 of /linux/arch/blackfin/include/asm/cache.h, which is called from read barrier depends( ) function at line 44 of /linux/arch/blackfin/include/asm/system.h, which is called from “rcu_dereference check( )” spanning lines 327-334 of linux/include/linux/rcupdate.h, which is implemented by rcu_deference( ) at line 519 of linux/include/linux/rcupdate.h. Unfortunately, this approach imposes great overhead on the RCU readers that invoke this primitive, defeating much of the purpose of using RCU in the first place. These developments therefore motivate an RCU implementation that can run efficiently on cache-incoherent systems.